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DBMS > Apache IoTDB vs. HyperSQL vs. KeyDB vs. Microsoft Azure Table Storage

System Properties Comparison Apache IoTDB vs. HyperSQL vs. KeyDB vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonKeyDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsA Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelTime Series DBMSRelational DBMSKey-value storeWide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score3.49
Rank#87  Overall
#47  Relational DBMS
Score0.71
Rank#226  Overall
#33  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Websiteiotdb.apache.orghsqldb.orggithub.com/­Snapchat/­KeyDB
keydb.dev
azure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhsqldb.org/­web/­hsqlDocsFrame.htmldocs.keydb.dev
DeveloperApache Software FoundationEQ Alpha Technology Ltd.Microsoft
Initial release2018200120192012
Current release1.1.0, April 20232.7.2, June 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infobased on BSD licenseOpen Source infoBSD-3commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)All OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modesLinuxhosted
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesyesyes infoby using the Redis Search moduleno
SQL infoSupport of SQLSQL-like query languageyesnono
APIs and other access methodsJDBC
Native API
HTTP API infoJDBC via HTTP
JDBC
ODBC
Proprietary protocol infoRESP - REdis Serialization ProtocoRESTful HTTP API
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
All languages supporting JDBC/ODBC
Java
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesJava, SQLLuano
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnoneMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Strong eventual consistency with CRDTs
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDOptimistic locking, atomic execution of commands blocks and scriptsoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesfine grained access rights according to SQL-standardsimple password-based access control and ACLAccess rights based on private key authentication or shared access signatures

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More resources
Apache IoTDBHyperSQL infoalso known as HSQLDBKeyDBMicrosoft Azure Table Storage
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